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Sprache: Englisch
Verlag: Dordrecht - Heidelberg - London - New York : Springer Verlag,, 2009
Anbieter: Antiquariat Dr. Josef Anker, Kiefersfelden, BAY, Deutschland
INHALT: 1. Introduction; 2. Unidimensional Item Response Theory Models; 3. Historical Background for Multidimensional Item Response Theory; 4. Multidimensional Item Response Theory Models; 5. Statistical Descriptions of Item and Test Functioning; 6. Estimation of Item and Person Parameters; 7. Analyzing the Structure of Test Data; 8. Transforming Parameter Estimates to a Specified Coordinate System; 9. Linking and Scaling; 10. Computerized Adaptive Testing Using MIRT; References; Index. Bibl.-Exemplar mit Rückenschild und Stempeln. Kanten leicht berieben, ansonsten recht guter Zustand Sprache: Englisch Gewicht in Gramm: 950 IX + 353 S., zahlreiche Tabellen und graphische Darstellungen, 24 x 16 cm, Pappband.
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Sprache: Englisch
Verlag: Guilford Publications, US, 2022
ISBN 10: 1462547753 ISBN 13: 9781462547753
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In den WarenkorbHardback. Zustand: New. Noted for addressing both the "hows" and "whys" of item response theory (IRT), this text has been revised and updated with the latest techniques (multilevel models, mixed models, and more) and software packages. Simple to more complex models are covered in consistently formatted chapters that build sequentially. The book takes the reader from model development through the fit analysis and interpretation phases that would be performed in practice. To facilitate understanding, common data sets are used across chapters, with the examples worked through for increasingly complex models. Exemplary model applications include free (BIGSTEPS, NOHARM, Facets, R packages) and commercial (BILOG-MG, flexMIRT, SAS, WINMIRA, SPSS, SYSTAT) software packages. The companion website provides data files and online-only appendices. New to This Edition *Chapter on multilevel models. *New material on loglinear models, mixed models, the linear logistic trait model, and fit statistics. *Many additional worked-through examples. *Updated guidance on software; now includes R, SAS, and flexMIRT.
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Zustand: New. Softcover reprint of the original 1st ed. 2018 edition NO-PA16APR2015-KAP.
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Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
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Sprache: Englisch
Verlag: Springer International Publishing, 2019
ISBN 10: 3030063720 ISBN 13: 9783030063726
Anbieter: preigu, Osnabrück, Deutschland
Taschenbuch. Zustand: Neu. Exploring the Mathematical Education of Teachers Using TEDS-M Data | Maria Teresa Tatto (u. a.) | Taschenbuch | xxiv | Englisch | 2019 | Springer International Publishing | EAN 9783030063726 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Sprache: Englisch
Verlag: Springer International Publishing, Springer International Publishing, 2019
ISBN 10: 3030063720 ISBN 13: 9783030063726
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book uses the publicly available TEDS-M data to answer such questions as: How does teacher education contribute to the learning outcomes of future teachers Are there programs that are more successful than others in helping teachers learn to teach mathematics How does the local and national policy environment contribute to teacher education outcomes It invites readers to explore these questions across a large number of international settings.The importance of preparing future mathematics teachers has become a priority across many nations. Across the globe nations have allocated resources and expertise to this endeavour. Yet in spite of the importance accorded to teacher education not much is known about different approaches to preparing knowledgeable teachers and whether these approaches do in fact achieve their purpose. The Mathematics Teacher Education and Development Study (TEDS-M) is the first, and to date the only, cross-national study using scientific and representative samples to provide empirical data on the knowledge that future mathematics teachers of primary and secondary school acquire in their teacher education programs. The study addresses the central importance of teacher knowledge in learning to teach mathematics by examining variation in the nature and influence of teacher education programs within and across countries.The study collected data on teacher education programs structure, curriculum and opportunities to learn, on teacher educators' characteristics and beliefs, and on future mathematics teachers' individual characteristics, beliefs, and mathematics and pedagogical knowledge across 17 countries providing a unique opportunity to explore enduring questions in the field.
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In den WarenkorbHardcover. Zustand: Brand New. 604 pages. 9.25x6.10x1.38 inches. In Stock.
Sprache: Englisch
Verlag: Springer International Publishing, 2018
ISBN 10: 3319921436 ISBN 13: 9783319921433
Anbieter: AHA-BUCH GmbH, Einbeck, Deutschland
Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book uses the publicly available TEDS-M data to answer such questions as: How does teacher education contribute to the learning outcomes of future teachers Are there programs that are more successful than others in helping teachers learn to teach mathematics How does the local and national policy environment contribute to teacher education outcomes It invites readers to explore these questions across a large number of international settings.The importance of preparing future mathematics teachers has become a priority across many nations. Across the globe nations have allocated resources and expertise to this endeavour. Yet in spite of the importance accorded to teacher education not much is known about different approaches to preparing knowledgeable teachers and whether these approaches do in fact achieve their purpose. The Mathematics Teacher Education and Development Study (TEDS-M) is the first, and to date the only, cross-national study using scientific and representative samples to provide empirical data on the knowledge that future mathematics teachers of primary and secondary school acquire in their teacher education programs. The study addresses the central importance of teacher knowledge in learning to teach mathematics by examining variation in the nature and influence of teacher education programs within and across countries.The study collected data on teacher education programs structure, curriculum and opportunities to learn, on teacher educators' characteristics and beliefs, and on future mathematics teachers' individual characteristics, beliefs, and mathematics and pedagogical knowledge across 17 countries providing a unique opportunity to explore enduring questions in the field.
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In den WarenkorbHardcover. Zustand: Brand New. 256 pages. 9.25x6.14x0.79 inches. In Stock.
Sprache: Englisch
Verlag: Guilford Publications, US, 2022
ISBN 10: 1462547753 ISBN 13: 9781462547753
Anbieter: Rarewaves.com UK, London, Vereinigtes Königreich
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In den WarenkorbHardback. Zustand: New. Noted for addressing both the "hows" and "whys" of item response theory (IRT), this text has been revised and updated with the latest techniques (multilevel models, mixed models, and more) and software packages. Simple to more complex models are covered in consistently formatted chapters that build sequentially. The book takes the reader from model development through the fit analysis and interpretation phases that would be performed in practice. To facilitate understanding, common data sets are used across chapters, with the examples worked through for increasingly complex models. Exemplary model applications include free (BIGSTEPS, NOHARM, Facets, R packages) and commercial (BILOG-MG, flexMIRT, SAS, WINMIRA, SPSS, SYSTAT) software packages. The companion website provides data files and online-only appendices. New to This Edition *Chapter on multilevel models. *New material on loglinear models, mixed models, the linear logistic trait model, and fit statistics. *Many additional worked-through examples. *Updated guidance on software; now includes R, SAS, and flexMIRT.